Psychiatry

Leveraging Novel Technologies and Artificial Intelligence to Advance Practice-Oriented Research.

Mental health services are experiencing notable transformations as innovative technologies and artif...

Depressive Disorder Recognition Based on Frontal EEG Signals and Deep Learning.

Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering bo...

Using natural language processing to increase prediction and reduce subgroup differences in personnel selection decisions.

The purpose of this research is to demonstrate how using natural language processing (NLP) on narrat...

Ensemble Approach to Combining Episode Prediction Models Using Sequential Circadian Rhythm Sensor Data from Mental Health Patients.

Managing mood disorders poses challenges in counseling and drug treatment, owing to limitations. Cou...

Predicting Autism from Head Movement Patterns during Naturalistic Social Interactions.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized in part by difficulti...

Development of immersive learning framework (ILF) in achieving the goals of higher education: measuring the impact using a pre-post design.

Emerging technological tools like Artificial Intelligence-based Chatbots, digital educational altern...

Integrating street view images and deep learning to explore the association between human perceptions of the built environment and cardiovascular disease in older adults.

Understanding how built environment attributes affect health remains important. While many studies h...

Measurement scales of mental health related to climate change: a scoping review protocol using artificial intelligence.

INTRODUCTION: Human actions have influenced climate changes around the globe, causing extreme weathe...

Predicting individual cases of major adolescent psychiatric conditions with artificial intelligence.

Three-quarters of lifetime mental illness occurs by the age of 24, but relatively little is known ab...

Natural language processing for mental health interventions: a systematic review and research framework.

Neuropsychiatric disorders pose a high societal cost, but their treatment is hindered by lack of obj...

[Digitization and Machine Learning in Psychotherapy Research and Clinical Practice - Potentials and Problems].

Risk of data leakage in estimating the diagnostic performance of a deep-learning-based computer-aided system for psychiatric disorders.

Deep-learning approaches with data augmentation have been widely used when developing neuroimaging-b...

Memristors based on NdNiO nanocrystals film as sensory neurons for neuromorphic computing.

By mimicking the behavior of the human brain, artificial neural systems offer the possibility to fur...

Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation.

Insufficiency of training data is a persistent issue in medical image analysis, especially for task-...

The future of psychiatry with artificial intelligence: can the man-machine duo redefine the tenets?

As one of the largest contributors of morbidity and mortality, psychiatric disorders are anticipated...

Current status, challenges and future prospects in computational psychiatry: a narrative review.

BACKGROUND: Computational psychiatry is an area of scientific knowledge which lies at the intersecti...

Machine learning techniques in diagnostics and prediction of the clinical features of schizophrenia: a narrative review.

BACKGROUND: Schizophrenia is a severe psychiatric disorder associated with a significant negative im...

Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia.

(SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations,...

Systematic review of machine learning in PTSD studies for automated diagnosis evaluation.

Post-traumatic stress disorder (PTSD) is frequently underdiagnosed due to its clinical and biologica...

Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals.

Mobile sensing is a ubiquitous and useful tool to make inferences about individuals' mental health b...

Machine Learning Differentiation of Autism Spectrum Sub-Classifications.

PURPOSE: Disorders on the autism spectrum have characteristics that can manifest as difficulties wit...